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Kiri L. Wagstaff

Jet Propulsion Laboratory, California Institute of Technology

Using Machine Learning to Reduce Observational Biases When Detecting New Impacts on Mars


Jul 12, 2022
Kiri L. Wagstaff, Ingrid J. Daubar, Gary Doran, Michael J. Munje, Valentin T. Bickel, Annabelle Gao, Joe Pate, Daniel Wexler

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* Icarus, vol. 386 (2022) 
* 17 pages, 10 figures, 2 tables (Author's preprint, accepted version) 

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Hidden Heterogeneity: When to Choose Similarity-Based Calibration


Feb 03, 2022
Kiri L. Wagstaff, Thomas G. Dietterich

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* Draft version currently under review. Do not cite. Comments and feedback welcome! 33 pages, 10 figures 

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Integrating Novelty Detection Capabilities with MSL Mastcam Operations to Enhance Data Analysis


Mar 23, 2021
Paul Horton, Hannah R. Kerner, Samantha Jacob, Ernest Cisneros, Kiri L. Wagstaff, James Bell

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* 8 pages, 5 figure, accepted and presented at IEEE Aerospace Conference 2021 

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Visualizing Image Content to Explain Novel Image Discovery


Aug 14, 2019
Jake H. Lee, Kiri L. Wagstaff

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* Under Review 

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Interpretable Discovery in Large Image Data Sets


Jun 21, 2018
Kiri L. Wagstaff, Jake Lee

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* Presented at the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018), Stockholm, Sweden 

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